A plant growth model for integrated weed management in direct-seeded rice: I. Development and sensitivity analyses of monoculture growth

A new model, DSRICE1, was developed to analyze weed management strategies in direct-seeded rice (Oryza sativa) systems. Previous rice models have not accounted for important cultural and weed management factors in direct-seeded systems, such as growth from seeds and water-depth effects on plant growth. Here we describe the development and sensitivity analysis of DSRICE1 for monoculture rice growth under water-seeded conditions. DSRICE1 is largely process-based and includes all standard weed management practices except fertility. Simulation inputs include latitude, daily solar radiation, daily maximum and minimum temperatures, water depth, and seed rate. Phenology depends on thermal units. Growth begins with seed storage mobilization to seedlings, and photosynthesis starts when the first leaf is extended. Canopy light dynamics depend on leaf and stem area distributions for both live and dead dry mass, and on water depth when submerged. Water-depth effects were explicitly simulated as reflection and attenuation of light. Model analyses revealed that parameter sensitivities varied over time. Some parameters were always important, while the effects of others were limited to particular parts of the season. Judged over the whole season, the most important parameters were for photosynthesis and light capture. Unlike in most monoculture simulations, early height gain rate was important in DSRICE1 because it determined when plants emerged from the water into full light. Analyses of model structure and specifications revealed that predictions were significantly affected by the use of skewed live leaf area distributions and the non-rectangular hyperbola for the light response curve, and the inclusion of waterdepth and dead canopy dry mass effects on canopy light dynamics. The cropping system and management processes simulated in DSRICE1 had important effects on model predictions of rice growth. Explicit consideration of these factors distinguishes DSRICE1 from other rice growth models, and may lead to better simulation analyses of system interactions with plant growth and weed management strategies. # 1999 Elsevier Science B.V. All rights reserved.

[1]  T. Foin,et al.  A plant growth model for integrated weed management in direct-seeded rice. III. Interspecific competition for light , 1999 .

[2]  I. R. Johnson,et al.  A model of instantaneous and daily canopy photosynthesis , 1984 .

[3]  T. R. Migo,et al.  Understanding crop-weed interaction in field situations. , 1993 .

[4]  N. McRoberts.  Ecology and integrated farming systems: Ed. by D. M. Glen, M. P. Greaves and H. M. Anderson. ISBN 0 471 95534-5. (329 pp; £49.00) Chichester, UK, John Wiley & Sons , 1996 .

[5]  T. Setter,et al.  Physiology and Genetics of Submergence Tolerance in Rice , 1997 .

[6]  S. K. De Datta,et al.  Technology Development and the Spread of Direct-Seeded Flooded Rice in Southeast Asia , 1986, Experimental Agriculture.

[7]  G. W. Cussans,et al.  Integrated weed management. , 1995 .

[8]  B. Miller,et al.  Plant Population Effects on Growth and Yield in Water-Seeded Rice , 1991 .

[9]  D. R. Miller,et al.  Sensitivity analysis and validation of simulation models , 1974 .

[10]  C. L. Elmore,et al.  A Reintroduction to Integrated Weed Management , 1996, Weed Science.

[11]  T. Foin,et al.  Phenotypic plasticity of Ammannia spp. in competition with rice , 1997 .

[12]  Martin J. Kropff,et al.  Modelling Crop-Weed Interactions , 1993 .

[13]  J. Norman,et al.  Modelling of solar irradiance, leaf energy budget and canopy photosynthesis , 1993 .

[14]  J. Goudriaan,et al.  A simple and fast numerical method for the computation of daily totals of crop photosynthesis. , 1986 .

[15]  B. C. Miller,et al.  A study of rice growth and development designed to develop CARICE: A rice growth model for scheduling management actions and evaluating management strategies under California's direct seeded, continuously flooded culture. , 1990 .

[16]  D. Datta,et al.  Principles and Practices of Rice Production , 1981 .

[17]  M. L. Peterson,et al.  The Seedling Establishment of Rice Under Water in Relation to Temperature and Dissolved Oxygen 1 , 1962 .

[18]  S. Yoshida.  Fundamentals of rice crop science , 1981 .

[19]  M. J. Kropff,et al.  Applications of Systems Approaches at the Field Level , 1997, Systems Approaches for Sustainable Agricultural Development.

[20]  Roger D. Cousens,et al.  The use of Biologically Realistic Equations to Describe the Effects of Weed Density and Relative Time of Emergence on Crop Yield , 1987, Weed Science.

[21]  B. Graf,et al.  Modelling the competition for light and nitrogen between rice and Echinochloa crus-galli , 1992 .

[22]  L. T. Evans,et al.  Some physiological aspects of the domestication and improvement of rice (Oryza spp.) , 1983 .

[23]  Curtis F. Gerald.  Applied numerical analysis , 1970 .

[24]  W. R. Coffman,et al.  Rainfed lowland rice improvement. , 1996 .

[25]  Andrew R. Watkinson,et al.  Modelling the Population Dynamics of an Arable Weed and Its Effects Upon Crop Yield , 1986 .

[26]  E. Schulze,et al.  Leaf nitrogen, photosynthesis, conductance and transpiration : scaling from leaves to canopies , 1995 .

[27]  James E. Hill,et al.  IPM: Managing water for weed control in rice , 1990 .

[28]  J. Wolfowitz,et al.  Introduction to the Theory of Statistics. , 1951 .

[29]  Photosynthesis and Production in a Changing Environment , 1993 .

[30]  C. J. Doyle,et al.  Mathematical models in weed management , 1991 .

[31]  C.J.T. Spitters,et al.  Separating the diffuse and direct component of global radiation and its implications for modeling canopy photosynthesis Part II. Calculation of canopy photosynthesis , 1986 .

[32]  Lloyd T. Wilson,et al.  Parameterization, verification, and validation of a physiologically complex age-structured rice simulation model , 1998 .

[33]  M. Jackson,et al.  Comparison of Growth Responses of Barnyard Grass (Echinochloa oryzoides) and Rice (Oryza sativa) to Submergence, Ethylene, Carbon Dioxide and Oxygen Shortage , 1991 .

[34]  D. Wyse.  New Technologies and Approaches for Weed Management in Sustainable Agriculture Systems , 1994, Weed Technology.

[35]  H. Berge,et al.  Simulation of Ecophysiological Processes of Growth in Several Annual Crops , 1989 .

[36]  J. Goudriaan,et al.  The bare bones of leaf-angle distribution in radiation models for canopy photosynthesis and energy exchange , 1988 .

[37]  I. R. Johnson,et al.  Plant and Crop Modelling: A Mathematical Approach to Plant and Crop Physiology , 1990 .

[38]  D. Bayer,et al.  Photosynthetic Response of Flooded Rice (Oryza sativa) and Three Echinochloa Species to Changes in Environmental Factors , 1993, Weed Science.

[39]  Marie-Laure Navas,et al.  Using plant population biology in weed research : a strategy to improve weed management , 1991 .

[40]  M. Kropff,et al.  Improving rice tolerance to barnyardgrass through early crop vigour: simulations with INTERCOM , 1997 .

[41]  Susan E. Weaver,et al.  Use of Ecophysiological Models for Crop-Weed Interference: Relations Amongst Weed Density, Relative Time of Weed Emergence, Relative Leaf Area, and Yield Loss , 1992, Weed Science.

[42]  B. S. Vergara,et al.  Improved Semidwarf Rice Lines with Tolerance to Submergence of Seedlings , 1993 .

[43]  B. S. Vergara,et al.  Environmental Effects on the Resistance of Rice Seedlings to Complete Submergence , 1972 .

[44]  M. Kropff,et al.  Possibility of Increasing Yield Potential of Rice by Reducing Panicle Height in the Canopy. I. Effects of Panicles on Light Interception and Canopy Photosynthesis. , 1995 .

[45]  T. Foin,et al.  CARICE: A Rice Model for Scheduling and Evaluating Management Actions , 1993 .

[46]  James E. Hill,et al.  Rice weed control: current technology and emerging issues in temperate rice , 1994 .

[47]  B. Acock,et al.  An adequate model of photosynthesis—I Parameterization, validation and comparison of models , 1996 .

[48]  C. Willmott.  ON THE VALIDATION OF MODELS , 1981 .

[49]  M. Yamauchi,et al.  Rice seedling establishment as affected by cultivar, seed coating with calcium peroxide, sowing depth, and water level , 1995 .

[50]  Kenneth J. Boote,et al.  Modeling Photosynthesis of Row Crop Canopies , 1994 .

[51]  H. Greenway,et al.  Submergence of rice. II: Adverse effects of low CO2 concentrations , 1989 .

[52]  Y. Yamasue,et al.  Productive Structures of Rice and Echinochloa oryzicola Vasing. in Mixed Stands , 1998 .

[53]  Martin J. Kropff,et al.  Relationship between Leaf Photosynthesis and Nitrogen Content of Field-Grown Rice in Tropics , 1995 .

[54]  T. Foin,et al.  A plant growth model for integrated weed management in direct-seeded rice II. Validation testing of water-depth effects and monoculture growth , 1999 .

[55]  C. Swanton,et al.  Integrated Weed Management: The Rationale and Approach , 1991, Weed Technology.

[56]  T. Foin,et al.  A temperature-based model of direct-, water-seeded rice (Oryza sativa) stand establishment in California , 1998 .

[57]  M. Kropff,et al.  Applications of an Ecophysiological Model for Irrigated Rice (Oryza sativa)-Echinochloa Competition , 1996, Weed Science.

[58]  B. Graf,et al.  A simulation model for the dynamics of rice growth and development: Part I—The carbon balance , 1990 .

[59]  J. Goudriaan,et al.  SEPARATING THE DIFFUSE AND DIRECT COMPONENT OF GLOBAL RADIATION AND ITS IMPLICATIONS FOR MODELING CANOPY PHOTOSYNTHESIS PART I. COMPONENTS OF INCOMING RADIATION , 1986 .

[60]  D. Hall.  Photosynthesis and production in a changing environment : a field and laboratory manual , 1993 .

[61]  Martin J. Kropff,et al.  Can simulation models help design rice cultivars that are more competitive against weeds , 1997 .

[62]  M. J. Robertson,et al.  Relationships between internode elongation, plant height and leaf appearance in maize , 1994 .